Abstract
<abstract><p>The perception of comparison measures is vitally significant in more or less every scientific field. They have many practical implementations in areas such as medicine, molecular biology, management, meteorology, etc. In this article, novel similarity, distance, and correlation comparison measures for Pythagorean $ m $-polar fuzzy sets are proposed. The leading qualities of these comparison measures are investigated. The numerical examples are provided to demonstrate their formulation. In P$ m $FSs, elements are allowed to duplicate finitely, which supports the usage of the measures put forward in here-and-now situations where we ponder time and again to reach some decision. The three algorithms are proposed to discuss the applications of comparison measures for P$ m $FSs in robotics and movie recommender systems.</p></abstract>
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